Not applicable.
The present invention relates generally to automotive driver aids and, more particularly, to a path prediction system and method for use with adaptive cruise control and collision avoidance systems for an automotive vehicle, the path prediction system tracking targets in the same highway lane as the vehicle.
In view of the improvements in the technology of automotive features, there is an ongoing opportunity to provide features that enhance driver convenience. One possible area of increased automobile convenience involves the vehicle""s cruise control system. A cruise control system permits an operator to set a predetermined speed of travel and controls the vehicle to maintain the predetermined speed. Hereinafter, the driver""s vehicle may be referred to as the xe2x80x9chost vehicle.xe2x80x9d
When employing the cruise control system, as the host vehicle approaches an obstacle in the highway, such as another vehicle in the driver""s lane, driver attention and intervention are necessary to override the cruise control system by actuating the host vehicle""s brakes and thereby avoid a collision.
To enhance the convenience of cruise control systems, xe2x80x9cintelligentxe2x80x9d cruise control systems have been suggested. Intelligent cruise control systems typically include a detector for detecting obstacles in the path of the vehicle and a controller for actuating the vehicle""s brakes and overriding the cruise control system in response to the detection of obstacles. Advantageously, intelligent cruise control systems can reduce the dependence on the driver for avoiding collisions.
Another possible area of increased automotive convenience is in collision avoidance systems. Like intelligent cruise control systems, collision avoidance systems generally include a detector for detecting obstacles in the path of the host vehicle and a controller for actuating the vehicle""s brakes in response to detected obstacles in order to avoid collisions.
In both the intelligent cruise control and collision avoidance applications, it is necessary to provide a detector capable of accurately and reliability detecting objects in the path of the vehicle. Such a detector must be relatively insensitive to the relative location of the automobile and obstacles. One problem with cruise control systems and collision avoidance systems, however, is that they can stop detecting obstacles in front of the host vehicle as the obstacle or host vehicle turns a corner. These systems are also susceptible to reduced effectiveness under certain environmental conditions, such as precipitation, fog or haze, high humidity, and extremes of temperature.
It would, therefore, be desirable to provide a system that is capable of detecting the presence of an obstacle in the forward path of a vehicle when either or both of the vehicle and the obstacle are traveling on either a straight or curved path.
In view of the above-stated needs and in accordance with the present invention, it has been recognized that combining the need for increased automotive convenience with the usefulness and desirability of obstacle detection leads to the problem of providing a path prediction system and method which is simple, accurate, cost-effective and reliable, given the environmental and other operating conditions under which such a system and method must operate. It would, therefore, be desirable to fill the need for a system and method that provides a reliable indication of the presence of obstacles forward of and in the same highway lane as an automotive vehicle.
In accordance with the principles of the present invention, there is disclosed herein a system for detecting objects in a predicted path of a host vehicle moving on a highway lane. The detecting system includes a forward looking sensor for providing range, angle and velocity data for objects within a field of view in front of the vehicle. The detecting system also includes measuring systems for providing velocity and yaw rate data for the host vehicle. The detecting system further includes a processing system responsive to the forward looking sensor and the measuring systems for calculating an estimated path of the vehicle based on its velocity and yaw rate, calculating estimated paths for each of the objects, determining the lateral distance of each object from the predicted path of the vehicle, and classifying each object as either in or out of the highway lane of the vehicle.
In a preferred embodiment of the present invention, the forward looking sensor comprises a radar system and the yaw rate measuring system comprises a gyrocompass or other angular rate sensor.
Further in accordance with the principles of the present invention, there is disclosed herein a method for detecting objects in a predicted path of a vehicle moving on a highway lane. The method is for use in a system including a forward looking sensor for providing range, angle and velocity data for objects within a field of view in front of the vehicle, measuring systems for providing velocity and yaw rate data for the vehicle, and a processing system responsive to the forward looking sensor and the measuring systems. The method comprises the steps of (a) calculating an estimated path of the vehicle based on its velocity and yaw rate; (b) calculating estimated paths for each of the objects; (c) determining the lateral distance of each object from the predicted path of the vehicle; and (d) classifying each object as either in or out of the highway lane of the vehicle.
Still further in accordance with the principles of the present invention, there is disclosed herein an additional method for detecting targets in a predicted path of a host vehicle moving on a highway lane. The method is for use in a system including a forward looking radar system for providing range, angle and velocity data for targets within a field of view in front of the host vehicle, measuring systems for providing velocity and yaw rate data for the host vehicle, and a processing system responsive to the radar and measuring systems. The method comprises the steps of (a) collecting data inputs from the forward looking radar system and the measuring systems, and deriving acceleration and lateral velocity target data therefrom; (b) calculating a host vehicle path estimate from the velocity and yaw rate data; (c) propagating target position histories with the host vehicle path estimate; (d) propagating target positions forward with longitudinal and lateral target position state vectors; (e) calculating polynomial curve fits for host vehicle and target position vectors; (f) generating the predicted path by correlating host vehicle and target paths and then fusing the target paths as a weighted average; (g) comparing target cross range positions to the predicted path and classifying targets as in-lane or out-of-lane with respect to the highway lane of the host vehicle; (h) receiving updated data from the forward looking radar system; and (i) repeating steps (a) through (h) continuously.
The method cited immediately above includes a process of testing for a highway lane change by the host vehicle. This process includes confirming such a highway lane change by comparing the integrated yaw rate to each target heading coefficient to see if it is equal and opposite, confirming that the majority of targets are moving in the opposite direction of the host vehicle, and noting that the opposite direction motion has occurred at two consecutive data updates from the forward looking radar system.